> For the complete documentation index, see [llms.txt](https://docs.theiamarkerless.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.theiamarkerless.com/axiom-v2025/theia3d-documentation/getting-started/startup-window.md).
# Startup Window
Theia3D application startup window.
The startup window appears if ***Select GPUs on launch*** is enabled in the Theia3D [setup preferences](/axiom-v2025/theia3d-documentation/theia3d-dropdown-menus/settings-menu/setup-preferences.md).
## **GPU Selection**
Select which graphics card(s) to use when running Theia3D.
## **Person Detector Size**
Select which person detector to use when running Theia3D, and set the ***Skip frames*** count.
* Small: fastest, may be slightly less accurate than Default or Large.
* Default: recommended.
* Large: slowest, may be slightly more accurate than Default or Small (currently disabled).
***Skip frames*** sets the frame interval used during the analysis process to identify and track people. Default is 1, Maximum is 5. Increasing the Skip Frames value will speed up the analysis. The ***Skip frames*** value should not be used for fast movements recorded at relatively low frame rates, or movements with multiple closely-interacting individuals, as the person identification may be affected.
## **Joint Detector Size**
Select which joint detector to use when running Theia3D.
* Small: fastest, may be slightly less accurate than Large (currently disabled).
* Large: (default) slowest, may be slightly more accurate than Small.
* Add Hands: (available as a license add-on by special request) Include hand model, which improves hand tracking through localization. Requires camera views that are positioned specifically to capture the hands and upper body. Please reach out to for more information.
## **Listen Mode**
Available as a license add-on by special request.
Listen Mode allows a directory to be selected where data is saved during data collection. The selected directory will be actively monitored for new, unprocessed data which will be automatically analyzed as it is detected. This allows data to be processed during an active data collection session, enabling all processing to be completed by the end of the collection session.
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